The invention described herein may be manufactured and used by or for the Government of the United States of America for governmental purposes without the payment of any royalties thereon or therefor.
Incorporated herein by reference is a computer program listing appendix setting forth an inventive embodiment of computer source code. This computer program listing appendix is contained as a text document which was created on Jan. 8, 2003 in a CD-R compact disc which is now situated in the application file. The CD-R compact disc contains one data file, 41 KB, in ASCII file format, entitled xe2x80x9cuspto09721998computerprogramlistingappendix.xe2x80x9d
The present invention relates to reduction of the magnetic field of an object, more particularly to calibration pertaining to degaussing, and to methods and apparatuses for achieving same.
U.S. Naval combatants are equipped with systems of degaussing coils, the purpose of which is to compensate the magnetic field of the ship, thereby reducing the vessel""s vulnerability to a mine threat. In order to perform effectively, it is necessary that a ship""s degaussing coil system be calibrated.
The method currently used to calibrate a ship""s degaussing coil system includes adjusting the electrical current flowing in each coil, and the number of turns in each coil, until the ship""s peak vertical magnetic field, or signature, located at a beam""s depth under the keel, has been reduced to a specified limit. This is accomplished by ranging the ship (e.g., at a xe2x80x9cMagnetic Silencing Facilityxe2x80x9d) to determine it""s existing magnetic field, consulting a handbook of coil effects and selecting the coil or coils which produce a magnetic peak nearest the peak in the ship""s existing magnetic field, and adjusting the current and turns in that coil or coils to compensate for and reduce the peak in the ship""s field. However, this method is limited to adjusting one or a few coils at a time, and becomes more difficult to implement as the number of coils in a degaussing system increases.
Another method for calibrating systems of degaussing coils has been used in the research model laboratory for over twenty years. This method includes performing a least-mean-squared-error (LMSE) fit of all of the model degaussing coil effects to the model ship""s magnetic signature, using a computer. This method enables better magnetic signature reduction, as the impact of all coils in the system can be calculated and utilized at once. This computer-assisted xe2x80x9cwholisticxe2x80x9d approach has been used in the field recently and has met with success in reducing ship magnetic signatures to levels below that which is capable using the manual xe2x80x9ccoil-by-coilxe2x80x9d approach described hereinabove. However, this method is limited to minimizing the average squared error between the ship signature (or signals derived from the ship signature) and a linear combination of the coil effects (or signals derived from the coil effects); it cannot be used, for example, to minimize the peak residual magnetic field signature.
Accordingly, there is a need for a degaussing coil methodology which can be efficiently implemented for practically any number of coils, and which is capable of achieving minimization of any signal derived from the degaussed signaturexe2x80x94not merely minimization of the mean squared error between the undegaussed signature and the coil effects.
In view of the foregoing, it is an object of the present invention to provide method and apparatus for calibrating a system of degaussing coils located around or inside an entity (such as a ship), in order to reduce the magnetic field of the entity.
It is a further object of the present invention to provide such method and apparatus which admits of practical application with respect to large as well as small numbers of degaussing coils.
It is another object of the present invention to provide such method and apparatus which can be implemented so as minimize virtually any signal derived from the degaussed signature.
In accordance with the present invention, a method is provided for calibrating a degaussing system for application to an object having a magnetic field associated therewith. The degaussing system is of the kind including at least one coil (more typically, plural coils) for conducting electrical current and for being proximately (e.g., peripherally) disposed in relation to said object. The inventive method comprises: designating at least one optimization parameter pertaining to the magnetic signature of the object in a degaussed condition; defining a current vector (e.g., mathematical array) containing at least one current value wherein each coil corresponds to a (at least one, but typically one) current value; and, executing a genetic algorithm so as to identify a solution of the current vector wherein the application of at least one current value to (at least one coil in) the degaussing system tends to optimize at least one optimization parameter.
Further provided in accordance with the present invention is a computer program product which comprises a computer useable medium having computer program logic recorded thereon for enabling a computer to calibrate a degaussing system for application to an object having a magnetic field associated therewith. The degaussing system is of the type which includes at least one coil for conducting electrical current and for being proximately disposed in relation to the object. The computer program logic comprises: means for enabling the computer to designate at least one optimization parameter pertaining to the magnetic signature of the object in a degaussed condition; means for enabling the computer to define a current vector containing at least one current value wherein each coil corresponds to a current value; and, means for enabling the computer to execute a genetic algorithm so as to identify a solution of the current vector wherein the application of at least one current value to the degaussing system tends to optimize at least one optimization parameter.
Also provided according to the present invention is a machine having a memory, such as a computer (e.g., that which includes a processor). The machine contains a data representation of the calibration of a degaussing system for application to an object having a magnetic field associated therewith. The degaussing system is of the type which includes at least one coil for conducting electrical current and for being proximately disposed in relation to the object. The data representation is generated, for availability for containment by the machine, by the method comprising: designating at least one optimization parameter pertaining to the magnetic signature of the object in a degaussed condition; defining a current vector containing at least one current value wherein each coil corresponds to a current value; and, executing a genetic algorithm so as to identify a solution of the current vector wherein the application of at least one current value to the degaussing system tends to optimize at least one optimization parameter.
Further provided in accordance with the present invention is a method for degaussing an object having a magnetic field associated therewith. The inventive method comprises: proximately disposing at least one coil in relation to the object; calibrating at least one coil; and, causing at least one coil to conduct electrical current in accordance with the calibrating. The calibrating includes: designating at least one optimization parameter pertaining to the magnetic signature of the object in a degaussed condition; defining a current vector containing at least one current value wherein each coil corresponds to a current value; and, executing a genetic algorithm so as to identify a solution of the current vector wherein the effectuation of at least one current value tends to optimize at least one optimization parameter.
Also provided according to the present invention is a system for degaussing an object having a magnetic field associated therewith. The inventive system comprises: at least one coil for conducting electrical current and for being proximately disposed in relation to the object; means for calibrating at least one coil; and, means for causing at least one coil to conduct electrical current in accordance with the calibrating. The calibrating includes: designating at least one optimization parameter pertaining to the magnetic signature of the object in a degaussed condition; defining a current vector containing at least one current value wherein each coil corresponds to a current value; and, executing a genetic algorithm so as to identify a solution of the current vector wherein the effectuation of at least one current value tends to optimize at least one optimization parameter.
The present invention represents a unique methodology for calibrating a degaussing coil system, and hence for practicing degaussing using a coil system which has been inventively calibrated. Notably featured by the present invention is the effectuation of a genetic algorithm for solving a mathematical vector (e.g., array) of electrical current values, wherein the solution objective is the optimization of one or more properties related to the degaussing of an object""s (e.g., a ship""s) magnetic signature. Generally according to preferred inventive practice, the subject degaussing coil system will include at least two coils. In the majority of inventive embodiments, the current vector will include plural current values which are in one-to-one correspondence with the plural coils. However, some inventive embodiments will involve a current vector in which certain (e.g., one, some or all) coils correspond to plural current values, or in which certain (e.g., one, some or all) current values correspond to plural coils.
An xe2x80x9cevolutionary algorithmxe2x80x9d is a computer-based problem-solving system which, in terms of design and implementation, is characterized by one or more computational models of one or more evolutionary processes. A particular genre of evolutionary algorithm is a xe2x80x9cgenetic algorithm,xe2x80x9d which represents a metaphor for the evolutionary and genetic processes in nature, commonly identified with Charles Darwin and Gregor Mendel. A genetic algorithm involves an iterative procedure which simulates, imitates or mimicks the genetic principles of Mendelian heredity along with the xe2x80x9csurvival-of-the-fittestxe2x80x9d principles of Darwinian evolution of species. A genetic algorithm does not yield a random result, albeit it involves indicia of randomness; rather, it can xe2x80x9cevolvexe2x80x9d a better-than-random, optimum-approaching solution to a problem.
The cyber-world (artificial life) mating of algorithmic chromosomes, pursuant to a genetic algorithm, resembles the real-world (real life) mating of biological chromosomes. A typical genetic algorithm begins with an initial xe2x80x9cpopulationxe2x80x9d of xe2x80x9cchromosomes.xe2x80x9d This first population of chromosomes, typically formulated in random fashion, can also be described as the first xe2x80x9cgeneration.xe2x80x9d A population is a set of solutions (chromosomes) to a problem, wherein each chromosome has plural components, or xe2x80x9cgenes.xe2x80x9d Each succeeding generation contains chromosomal xe2x80x9coffspringxe2x80x9d from the preceeding generation, similarly as occurs in the biological evolutionary genetic processes of natural selection and heredity. The final population of chromosomes contains the best solution to the problem; that is, the xe2x80x9cfittestxe2x80x9d chromosome among all the chromosomes in the last generation constitutes the ultimate or optimal solution.
According to typical genetic algorithms, chromosomes are selected (e.g., in pairs) and are combined with each other in a hybridizing (e.g., crossover) fashion whereby individual chromosomes are partitioned and the offspring chromosomes have combinations of characteristics (genes) from the parent chromosomes. For instance, according to a common genetic algorithmic combinative approach, chromosomes are repeatedly selected in pairs wherein each selected parent chromosomal pair produces an offspring chromosomal pair; that is, on each occasion, two parent chromosomes are selected and are combined (e.g., via a crossover procedure) to form two offspring chromosomes.
In addition, according to typical inventive embodiments, individual chromosomes will mutate on a sometimes (e.g., occasional) basis. Depending on the inventive embodiment, the mutation function can be applied in various ways to any of various pools of chromosomes. For instance, based on a certain (typically, low) probability, a percentage of offspring chromosomes will each be caused to randomly mutate (wherein one or more genes therein undergoes a change). According this kind of common genetic algorithmic mutative approach, a mutation function is applied to offspring chromosomes which have been engendered by selection and combination of parent chromosomes. As another approach, the mutation function can be applied to parent chromosomes prior to selection and combination thereof. Alternatively, the effecting of mutation can be determined in some other manner.
Built into the chromosome selection process is a bias toward more xe2x80x9cfitxe2x80x9d chromosomes and against less xe2x80x9cfitxe2x80x9d chromosomes; thus, the probabilities are weighted according to fitness as to which chromosomes of a given population are to become parents to the offspring of the next population. The term xe2x80x9croulette wheelxe2x80x9d is conventionally used to describe many such schemes having indicia of both randomness and bias. The weightedness or probability variation can be analogized to a xe2x80x9croulette wheelxe2x80x9d having variously sized slots corresponding to variously fit chromosomes. Another anology is a xe2x80x9clotteryxe2x80x9d methodology in which the respective numbers of ping-pong balls are commensurate with their respective fitnesses.
There are other examples of biasedly randomized arrangements wherein outcomes are basically left to chance, except that probabilities are higher or lower according to corresponding fitnesses. In any event, usually according to the present invention, this fitness-based selection is performed xe2x80x9cwith replacementxe2x80x9d; that is, the same chromosome can be selected more than once to be a parent. In other words, even when a chromosome is selected to be a parent, that selected chromosome remains in the pool of potential parent chromosomes and can be selected again. Therefore, after a roulette wheel is spun and the ball lands in a particular slot, all of the slots of a roulette wheel remain in place, the roulette wheel ready to be re-spun. In the context of the ping-pong ball analogy, after a bin is stirred, any ping-pong ball which is selected from the bin to be a parent will be returned to the bin, and the bin can subsequently be re-stirred.
Thus, according to many conventional genetic algorithms, the creation of each ensuing population entails fitness-based selection, hybridization and mutation with respect to the previous population. Generally, the tendency will be such that as the number of generations increases the population""s chromosomal pool will improve insofar as representing solutions to the problem. The evolutionary genetic process encourages the xe2x80x9csurvivalxe2x80x9d of the xe2x80x9cfittestxe2x80x9d solutions; by virtue of the xe2x80x9cselective pressurexe2x80x9d which favors the fittest, the population keeps improving as a whole. For instance, each succeeding generation will be at least slightly better on average than the preceeding generation, or will contain at least one chromosome which is at least slightly better than every chromosome in a preceeding generation.
An abundance of instructive literature has been published on genetic algorithms and on evolutionary algorithms in general. Incorporated herein by reference are the following two textbooks: David E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison Wesley Longman, Inc., New York, 1989; Melanie Mitchell, An Introduction to Genetic Algorithms, MIT Press, Cambridge, Mass., 1996. Also incorporated herein by reference are the following six articles: Peter Wayner, xe2x80x9cGenetic Algorithms: Programming Takes a Valuable Tip from Nature,xe2x80x9d BYTE, January 1991, pp 361-368; J. H. Holland, xe2x80x9cGenetic Algorithms,xe2x80x9d Scientific American, Volume 267, No. 1, 1992, pp 66-72; W. M. Spears et al., xe2x80x9cAn Overview of Evolutionary Computation,xe2x80x9d ECML ""93, Proceedings of the European Conference on Machine Learning, Vienna, Austria, Apr. 5-7, 1993, pp 442-459; Thomas Bxc3xa4ck et al., xe2x80x9cAn Overview of Evolutionary Algorithms for Parameter Optimization,xe2x80x9d Evolutionary Computation, Vol. 1, No. 1, 1993, pp 1-23; D. B. Fogel, xe2x80x9cAn Introduction to Simulated Evolutionary Optimization,xe2x80x9d IEEE Trans. Neural Networks, Vol. 5, No. 1, 1994, pp 3-14; David E. Goldberg, xe2x80x9cGenetic and Evolutionary Algorithms Come of Age,xe2x80x9d Communications of the ACM, Vol. 37, No. 3, 1994, pp 113-119; Zbigniew, Michalewixz, xe2x80x9cGenetic Algorithms+Data Structures=Evolution Programs,xe2x80x9d Springer-Verlag, New York, 1994.
The present invention uniquely features a genetic algorithm which xe2x80x9cevolvesxe2x80x9d an optimal (optimally tending) solution to the calibration of degaussing coils. According to many embodiments of this invention, the chromosomes are mathematical vectors (mathematical arrays) of electrical current values (genes). The first population of current vectors (chromosomes) is selected randomly. Each ensuing population of current vectors (chromosomes) arises from the previous population via a genetic algorithmic procedure including fitness-based selection of current vectors (chromosomes), combination (e.g., hybridization, as by crossover) of (e.g., pairs of) current vectors (chromosomes), and mutation (e.g., based on a relatively low random probability) of current vectors (chromosomes). The solution to the degaussing coil problem is represented by the current values (genes) contained in the fittest current vector (chromosome) which exists in the final population, i.e., the last generation.
In accordance with the present invention, a solution to the degaussing problem is found which is xe2x80x9coptimal.xe2x80x9d The optimal solution is not that which may be graphically envisioned as the single, maximum point on a curve which rises to the maximum point and falls therefrom. Rather, the optimal solution is that which may be graphically envisioned in the context of a curve which rises and continues to rise, approaching (e.g.,asymptotically in relation to a horizontal line representative of) a limit which constitutes xe2x80x9climitaryxe2x80x9d optimum, a theoretically approachable but elusive optimum; the optimal solution is a point which tends toward or approaches the limitary optimum. With each ensuing generation, or at least with groups of two or more ensuing generations, the solution takes a step closer to limitary optimum. The xe2x80x9coptimalxe2x80x9d solution is really a solution which tends to optimizexe2x80x94i.e., which tends toward or approaches the limitary optimal solution. It is nearly or approximately equal to the limitary optimal solution, or at least considerably closer to the limitary optimal solution than to a purely random solution.
Typically according to this invention, each current vector (chromosome) will have the same number of current values (genes), since the current vectors correspond to, and equal in number, the coils in the degaussing system. In his/her inventive design of the computer program, the inventive practitioner will consider the nature of the problem, including the number of current values (genes) in each current vector (chromosome), and will adjudge the appropriate size of the population as well as the appropriate number of generationsxe2x80x94such that an optimal (i.e., optimally tending) solution will be obtained. Once the present invention""s iterative process has repeated through a certain number of generations, a point will be reached wherein the xe2x80x9cfittestxe2x80x9d current vector (chromosome) in the population will represent a solution which, to at least a substantial degree or for all intents and purposes, is the limitary optimal solution. The inventive practitioner will generally seek an optimal solution in other words, a solution which tends to optimize degaussing, with respect to one or more selected optimization parameters, of the object being degaussed.
The inventive practitioner will preferably repeat the generational iterations a sufficient number of times so that this point of substantial or practical equivalence to the limitary optimum is reached. There are various approaches to mathematically incorporating such decision regarding number of generations into the inventive program. One approach is to establish a fixed number of generations in the program. This approach is feasible provided the inventive practitioner can be confident that implementation of this fixed number, in inventive application, will result in an optimal solution. Another approach to achieving an optimal solution is to establish the last generation (i.e., cessation of the inventive genetic evolution) to be that which fails to significantly differ from the preceeding generation in terms of fitness. Otherwise expressed, a propitious time to cease creating new generations is when a xe2x80x9cpoint of diminishing returnxe2x80x9d has been reached insofar as improving fitness; that is, a point has been reached wherein the difference in fitness from one generation to the next is minimal, negligible or virtually nonexistent.
This generation-to-generation fitness differential can be ascertained in various ways. For instance, the average of the respective fitness values of the current vectors (chromosomes) a preceeding population can be compared with the average of the respective fitness values of the current vectors (chromosomes) of a succeeding population; in effect, the xe2x80x9caveragexe2x80x9d fitness (e.g., arithmetic mean, median or mode) would constitute a measurement characterizing the overall fitness of a particular population. Or, as another example, along similar lines, the greatest (maximum) fitness value of a current vector (chromosome) of a preceeding population can be compared with the greatest (maximum) fitness value of a current vector (chromosome) of a succeeding population. When a stage has been reached wherein the fitness differential between consecutive generations is minimal, negligible or approximately nil, the inventive program""s iterative process can be stopped with the reasonable assurance that the solution thereby obtained (from among the set of current vectors in the final population) is about as good a solution as can be obtained.
The present invention represents a new approach to the calibration of combatant degaussing systems. This invention uses an evolution program to optimize various parameters of the degaussed magnetic signature. Typical embodiments of the inventive program incorporate a floating point genetic algorithm with arithmetic combination operators and a non-uniform mutation operator. Various fitness functions can be explored in accordance with the present invention, including but not limited to the following functions which are discussed herein: (i) optimization of root mean square (RMS); (ii) peak; (iii) peak rate of change (ROC); (iv) peak rate of change (ROC) in a signature segment; and, (v) distance of the degaussed signature from a desired goal signature. The present invention is applicable not only to ship degaussing coil systems but also to a variety of other (non-ship) degaussing coil systems.
The optimal degaussing (abbreviated xe2x80x9cODGxe2x80x9d or xe2x80x9cODxe2x80x9d) evolution program and method in accordance with the present invention has several advantages over previous degaussing methodologies. A propitious flexibility is afforded by the present invention in terms of what is being optimized; the inventive program and method can be adapted toward achieving one, two or several modesxe2x80x94indeed, practically any number of modesxe2x80x94of xe2x80x9coptimality.xe2x80x9d The present invention is not limited to minimizing the mean squared error between the undegaussed signature and the coil effects, but can be used to minimize any arbitrary criterion/criteria based on the residual signature obtained after combining the coil effects with the undegaussed signature. In accordance with the present invention, any signal derived from the degaussed signature can be minimized. For example, the degaussed signature can be applied to a certain type of mine, and the output of the mine can be used as the minimization criterion. Also, according to this invention, any combination of criteria can be used. For example, the mine sensor output can be minimized at the same time that the overall power consumption of the coil system is minimized.